Manager - Data Engineering

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or related field.
• 8-12 years of Data Engineering experience, with 3-5 years in a leadership or managerial role.
• Expertise in at least one major cloud platform: Azure (Data Lake, Databricks, Synapse, Data Factory), AWS (S3, Glue, EMR, Redshift), or GCP (BigQuery, Dataflow, DataProc).
• Strong proficiency in SQL, Python, and PySpark for ETL, data transformation, and automation.
• Experience with Big Data technologies (Hadoop, Spark) and modern data lake house architectures.
• Proficiency in dimensional and relational data modeling (Star, Snowflake schemas) with metadata management.
• Experience integrating data from on-premise systems, REST APIs, and third-party sources (SAP, Salesforce).
• Working knowledge of Power BI and data security frameworks, governance, and compliance best practices.
• Proven ability to lead distributed teams and manage project deliverables.
• Experience in budget planning and cost optimization for cloud infrastructure.
• Exposure to AI/ML frameworks and cloud-native AI services (Azure OpenAI, Amazon Bedrock, Google Vertex AI).
• Proficiency in English (spoken and written).
• Certification in Azure DP-203, AWS Data Analytics Specialty, or GCP Professional Data Engineer.
• Experience in global, multi-system, or large-scale data environments.
• Exposure to real-time or streaming data tools (Kafka, Event Hubs, Stream Analytics).
• Background in manufacturing or engineering organizations.
• Experience supporting data science or predictive analytics initiatives.
• Competencies and Abilities:
• Strong leadership, team-building, and mentoring capabilities.
• Excellent analytical thinking, problem-solving, and attention to detail.
• Strategic thinker with hands-on execution approach.
• Strong communication and stakeholder management skills across business and technical teams.
• Organized, systematic, and capable of managing multiple priorities under pressure.
• Self-motivated, reliable, and passionate about innovation and continuous improvement.
• Join us and work for a world-leader, with the benefits and training to reward your dedication and skills. Be part of a team where we are making the world a safer place.

Benefits

Additional Information

Duties / Key Responsibilities: Supervise and manage a team of Data Engineers, providing technical guidance, mentorship, performance review and support for professional development. Own the Data Lake architecture setup, maintenance, and optimization across the enterprise platform. Lead the design and implementation of data ingestion, transformation, and integration pipelines, including ETL/ELT workflows across enterprise systems such as SAP and Salesforce. Ensure compliance with data governance, privacy, and security standards in alignment with organizational policies. Define and implement data engineering best practices, including version control, CI/CD, performance tuning, and automation across all delivery activities. Oversee data quality frameworks, validation rules, and monitoring processes to ensure accuracy and consistency across the platform. Supervise migration and modernization initiatives for the data lake, ensuring seamless transitions and minimal disruption. Collaborate with Data Architects, Analytics teams, and IT stakeholders to deliver scalable technical solutions and analytics-ready data models. Monitor data platform resource usage and support cost-optimization efforts across cloud infrastructure while maintaining system performance and reliability. Contribute to the design of AI- and ML-ready data architecture and support the development of the data strategy and platform roadmap in collaboration with senior leadership. Technical Knowledge and Skills:

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